DRD2基因rs2587552多态性对儿童肥胖干预效果的影响：一项前瞻性、平行对照试验

doi:10.19723/j.issn.1671-167X.2023.03.008

摘要/Abstract

摘要：

目的: 在我国儿童中探索DRD2基因rs2587552多态性与肥胖干预效果的关联，为将来开展基于遗传背景的个性化儿童肥胖干预提供科学依据。方法: 基于一项儿童肥胖干预研究的多中心整群随机对照试验，纳入北京地区8所小学的382名儿童作为研究对象，采集唾液，提取DNA，检测DRD2基因rs2587552多态性，并分析基因与干预措施对儿童肥胖干预效果(包括体质量、体重指数、体重指数Z评分、腰围、臀围、腰臀比、腰围身高比和体脂百分比指标)的交互作用。结果: 干预组中未发现rs2587552多态性与儿童臀围和体脂百分比的变化相关(P>0.05)，而在对照组中，携带rs2587552位点A等位基因的儿童相比于非携带儿童，其臀围和体脂百分比升高更多(P < 0.001)。DRD2基因rs2587552多态性与干预措施对儿童臀围和体脂百分比存在交互作用(P分别为0.007和0.015)。与对照组相比，干预组携带A等位基因的儿童相比于非携带儿童，臀围下降(-1.30 cm，95%CI：-2.25~-0.35，P=0.007)，体脂百分比下降(-1.34%，95%CI：-2.42~-0.27，P=0.015)。显性与加性遗传模型的结果较为一致(臀围下降：-0.66 cm，95%CI：-1.28~-0.03，P=0.041;体脂百分比下降：-0.69%，95%CI：-1.40~0.02，P=0.056)。未发现rs2587552多态性与干预措施对其他儿童肥胖相关指标存在交互作用(P>0.05)。结论: 在DRD2基因rs2587552位点携带A等位基因的儿童对干预措施更加敏感，干预期间在臀围和体脂百分比指标上获得更多改善，提示未来可基于儿童rs2587552位点的基因型开展个性化的生活方式干预。

关键词: 儿童肥胖, 多态性，单核苷酸, 生活方式, 干预效果

Abstract:

Objective: To explore the association between rs2587552 polymorphism (has a strong lin-kage disequilibrium with rs1800497 which had been found in many studies to be related to obesity, r²=0.85) of DRD2 gene and the effect of a childhood obesity intervention in Chinese population, and provide a scientific basis for future personalized childhood obesity intervention based on genetic background. Methods: From a multi-center cluster randomized controlled trial studying the effect of a childhood obesity intervention, we enrolled 382 children from 8 primary schools (192 and 190 children from intervention and control groups, respectively) in Beijing as study subjects. Saliva was collected and DNA was extracted to detect the rs2587552 polymorphism of DRD2 gene, and the interactions between the gene and study arms on childhood obesity indicators [including body weight, body mass index (BMI), BMI Z-score, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio, and body fat percentage] were analyzed. Results: No association was found between rs2587552 polymorphism and the changes in hip circumference or body fat percentage in the intervention group (P>0.05). However, in the control group, children carrying the A allele at DRD2 rs2587552 locus showed a greater increase in hip circumference and body fat percentage compared with those not carrying A allele (P < 0.001). There were interactions between rs2587552 polymorphism of DRD2 gene and study arms on the changes in hip circumference and body fat percentage (P=0.007 and 0.015, respectively). Compared with the control group, children in the intervention group carrying the A allele at DRD2 rs2587552 locus showed decrease in hip circumference by (-1.30 cm, 95%CI: -2.25 to -0.35, P=0.007) and decrease in body fat percentage by (-1.34%, 95%CI: -2.42 to -0.27, P=0.015) compared with those not carrying A allele. The results were consistent between the dominant model and the additive model (hip circumfe-rence: -0.66 cm, 95%CI: -1.28 to -0.03, P=0.041; body fat percentage: -0.69%, 95%CI: -1.40 to 0.02, P=0.056). No interaction was found between rs2587552 polymorphism and study arms on the changes in other childhood obesity-related indicators (P>0.05). Conclusion: Children carrying the A allele at rs2587552 polymorphism of DRD2 gene are more sensitive to intervention and showed more improvement in hip circumference and body fat percentage after the intervention, suggesting that future personalized childhood obesity lifestyle intervention can be carried out based on the rs2587552 polymorphism of DRD2 gene.

Key words: Pediatric obesity, Polymorphism, single nucleotide, Life style, Intervention effect

中图分类号:

R179

陈敬,肖伍才,单蕊,宋洁云,刘峥. DRD2基因rs2587552多态性对儿童肥胖干预效果的影响：一项前瞻性、平行对照试验[J]. 北京大学学报（医学版）, 2023, 55(3): 436-441.

Jing CHEN,Wu-cai XIAO,Rui SHAN,Jie-yun SONG,Zheng LIU. Influence of rs2587552 polymorphism of DRD2 gene on the effect of a childhood obesity intervention: A prospective, parallel-group controlled trial[J]. Journal of Peking University (Health Sciences), 2023, 55(3): 436-441.

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参考文献 28

1	NCD Risk Factor Collaboration (NCD-RisC) .Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: A pooled analysis of 2 416 population-based measurement studies in 128.9 million children, adolescents, and adults[J].Lancet,2017,390(10113):2627-2642. doi: 10.1016/S0140-6736(17)32129-3
2	Dong Y , Jan C , Ma Y , et al.Economic development and the nutritional status of Chinese school-aged children and adolescents from 1995 to 2014: An analysis of five successive national surveys[J].Lancet Diabetes Endocrinol,2019,7(4):288-299. doi: 10.1016/S2213-8587(19)30075-0
3	The Lancet Public Health .Childhood obesity beyond COVID-19[J].Lancet Public Health,2021,6(8):e534. doi: 10.1016/S2468-2667(21)00168-7
4	Friedemann C , Heneghan C , Mahtani K , et al.Cardiovascular disease risk in healthy children and its association with body mass index: Systematic review and meta-analysis[J].BMJ,2012,345,e4759. doi: 10.1136/bmj.e4759
5	Quek YH , Tam WWS , Zhang MWB , et al.Exploring the association between childhood and adolescent obesity and depression: A meta-analysis[J].Obes Rev,2017,18(7):742-754. doi: 10.1111/obr.12535
6	Rankin J , Matthews L , Cobley S , et al.Psychological consequences of childhood obesity: Psychiatric comorbidity and prevention[J].Adolesc Health Med Ther,2016,7,125-146.
7	Geng T , Smith CE , Li C , et al.Childhood BMI and adult type 2 diabetes, coronary artery diseases, chronic kidney disease, and cardiometabolic traits: A mendelian randomization analysis[J].Diabetes Care,2018,41(5):1089-1096. doi: 10.2337/dc17-2141
8	Bleich SN , Vercammen KA , Zatz LY , et al.Interventions to prevent global childhood overweight and obesity: A systematic review[J].Lancet Diabetes Endocrinol,2018,6(4):332-346. doi: 10.1016/S2213-8587(17)30358-3
9	Feng L , Wei DM , Lin ST , et al.Systematic review and meta-analysis of school-based obesity interventions in mainland China[J].PLoS One,2017,12(9):e0184704. doi: 10.1371/journal.pone.0184704
10	Liu Z , Xu HM , Wen LM , et al.A systematic review and meta-analysis of the overall effects of school-based obesity prevention interventions and effect differences by intervention components[J].Int J Behav Nutr Phys Act,2019,16(1):95. doi: 10.1186/s12966-019-0848-8
11	Bouchard C , Tremblay A .Genetic influences on the response of body fat and fat distribution to positive and negative energy ba-lances in human identical twins[J].J Nutr,1997,127(Suppl 5):943S-947S.
12	do Nascimento GA , Leite N , Furtado-Alle L , et al.FTO rs9939609 does not interact with physical exercise but influences basal insulin metabolism in Brazilian overweight and obese adolescents[J].J Obes,2018,2018,3134026.
13	Zou ZC , Mao LJ , Shi YY , et al.Effect of exercise combined with dietary intervention on obese children and adolescents associated with the FTO rs9939609 polymorphism[J].Eur Rev Med Pharmacol Sci,2015,19(23):4569-4575.
14	Zlatohlavek L , Vrablik M , Motykova E , et al.FTO and MC4R gene variants determine BMI changes in children after intensive lifestyle intervention[J].Clin Biochem,2013,46(4/5):313-316.
15	Vogel CI , Boes T , Reinehr T , et al.Common variants near MC4R: Exploring gender effects in overweight and obese children and adolescents participating in a lifestyle intervention[J].Obes Facts,2011,4(1):67-75. doi: 10.1159/000324557
16	Mehta S , Melhorn SJ , Smeraglio A , et al.Regional brain response to visual food cues is a marker of satiety that predicts food choice[J].Am J Clin Nutr,2012,96(5):989-999. doi: 10.3945/ajcn.112.042341
17	Xiao WC, Chen J, Liu Z. The role of genetic variants in childhood obesity interventions: A systematic review and meta-analysis. PROSPERO 2022 CRD42022312177. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022312177.
18	Roth CL , Hinney A , Schur EA , et al.Association analyses for dopamine receptor gene polymorphisms and weight status in a longitudinal analysis in obese children before and after lifestyle intervention[J].BMC Pediatr,2013,13,197. doi: 10.1186/1471-2431-13-197
19	Barnard ND , Noble EP , Ritchie T , et al.D2 dopamine receptor Taq1A polymorphism, body weight, and dietary intake in type 2 diabetes[J].Nutrition,2009,25(1):58-65. doi: 10.1016/j.nut.2008.07.012
20	Fang YJ , Thomas GN , Xu ZL , et al.An affected pedigree member analysis of linkage between the dopamine D2 receptor gene TaqI polymorphism and obesity and hypertension[J].Int J Car-diol,2005,102(1):111-116. doi: 10.1016/j.ijcard.2004.05.010
21	Zhu JF , Chen LH , Yuan K , et al.Dopamine receptor D2 polymorphism is associated with alleviation of obesity after 8-year follow- up: A retrospective cohort study in obese Chinese children and adolescents[J].J Zhejiang Univ Sci B,2018,19(10):807-814. doi: 10.1631/jzus.B1800155
22	Liu Z , Gao P , Gao AY , et al.Effectiveness of a multifaceted intervention for prevention of obesity in primary school children in China: A cluster randomized clinical trial[J].JAMA Pediatr,2022,176(1):e214375. doi: 10.1001/jamapediatrics.2021.4375
23	de Onis M , Onyango AW , Borghi E , et al.Development of a WHO growth reference for school-aged children and adolescents[J].Bull World Health Organ,2007,85(9):660-667. doi: 10.2471/BLT.07.043497
24	中华人民共和国国家卫生和计划生育委员会. WS/T 586—2018学龄儿童青少年超重与肥胖筛查[S]. 北京: 中国标准出版社, 2018.
25	Marees AT , de Kluiver H , Stringer S , et al.A tutorial on conducting genome-wide association studies: Quality control and statistical analysis[J].Int J Methods Psychiatr Res,2018,27(2):e1608. doi: 10.1002/mpr.1608
26	Howie B , Marchini J , Stephens M .Genotype imputation with thousands of genomes[J].G3 (Bethesda),2011,1(6):457-470. doi: 10.1534/g3.111.001198
27	Cardel MI , Lemas DJ , Lee AM , et al.Taq1a polymorphism (rs1800497) is associated with obesity-related outcomes and die-tary intake in a multi-ethnic sample of children[J].Pediatr Obes,2019,14(2):e12470.
28	Goodarzi MO .Genetics of obesity: What genetic association stu-dies have taught us about the biology of obesity and its complications[J].Lancet Diabetes Endocrinol,2018,6(3):223-236. doi: 10.1016/S2213-8587(17)30200-0

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Characteristics	Intervention group (n=192)	Control group (n=190)	P
Age/years	9.55 ± 0.29	9.56 ± 0.31	0.596
Female	90 (46.87)	97 (51.05)	0.475
Overweight/Obesity	74 (38.54)	74 (38.95)	1.000
Obesity	48 (25.00)	41 (21.58)	0.503
Weight/kg	36.96±9.35	35.97±8.95	0.287
BMI/(kg/m²)	18.57±3.71	18.23±3.29	0.333
BMI Z-score	0.72±1.46	0.61±1.40	0.426
Waist circumference/cm	65.00±10.45	64.42±9.92	0.573
Hip circumference/cm	76.45±8.09	76.42±7.84	0.971
Waist-to-hip ratio	0.85±0.06	0.84±0.05	0.232
Waist-to-height ratio	0.46±0.07	0.46±0.06	0.735
Body fat percentage/%	21.16±10.77	20.25±9.43	0.379

Indicators	AA/AC (n=262)	GG (n=120)	P
Male	134 (51.15)	61 (50.83)
Overweight/Obesity	95 (36.26)	53 (44.17)	0.136
Obesity	59 (22.52)	30 (25.00)	0.576
Age/years	9.57±0.30	9.52±0.30
Weight/kg	36.38±9.28	36.65±8.91	0.592
BMI/(kg/m²)	18.35±3.59	18.51±3.33	0.573
BMI Z-score	0.63±1.46	0.74±1.35	0.440
Waist circumference/cm	64.59±10.41	64.97±9.70	0.592
Hip circumference/cm	76.29±8.06	76.76±7.75	0.425
Waist-to-hip ratio	0.84±0.06	0.84±0.05	0.932
Waist-to-height ratio	0.46±0.06	0.46±0.06	0.604
Body fat percentage/%	20.62±10.39	20.89±9.55	0.733

Obesity-related indicators	SNP’s effects in intervention group			SNP’s effects in control group			Interaction (intervention-control)
Obesity-related indicators	AA/AG (n=125)	GG(n=67)	P^a	AA/AG (n=137)	GG(n=53)	P^a	β coefficient (95%CI)^b	P^b
ΔWeight/kg	2.47±2.03	2.26±2.75	0.372	3.73±3.39	2.63±2.24	0.029	-0.738 (-1.880 to 0.404)	0.205
ΔBMI/(kg/m²)	-0.05±0.84	-0.15±1.20	0.507	0.50±1.30	-0.01±0.90	0.006	-0.430 (-0.910 to 0.049)	0.078
ΔBMI Z-score	-0.22±0.34	-0.30±0.52	0.268	0.005±0.64	-0.21±0.36	0.008	-0.162 (-0.372 to 0.049)	0.132
ΔWaist circumference/cm	1.20±3.30	0.72±2.94	0.289	1.65±2.84	0.62± 3.29	0.014	-0.702 (-2.039 to 0.635)	0.302
ΔHip circumference/cm	2.33±2.20	2.21±2.00	0.734	3.01±2.12	1.62±2.61	< 0.001	-1.302 (-2.251 to -0.353)	0.007
ΔWaist-to-hip ratio	-0.01±0.04	-0.01±0.04	0.471	-0.01±0.03	-0.01±0.03	0.826	0.003 (-0.011 to 0.017)	0.671
ΔWaist-to-height ratio	-0.01±0.02	-0.01±0.02	0.348	-0.004±0.02	-0.01±0.02	0.011	-0.006 (-0.015 to 0.004)	0.245
ΔBody fat percentage/%	-1.03±2.79	-1.10±2.01	0.894	0.46±2.30	-0.85±2.99	< 0.001	-1.342 (-2.419 to -0.266)	0.015